## Introduction to R Programming

**Certiology’s free R programming tutorial. If you have minimal programming knowledge and are using R as a beginner, you can understand all the general basic programming concepts and specific R concepts.**

R-project defines R as, “language and environment for statistical computing and graphics”.

Talking about the background and history, R is an implementation of S programming language, which was developed by Bell Laboratories for Statistical computing. S wan combined with lexical scoping to get R. Currently R development core team takes care of the maintenance of R which was initially developed by the University of Auckland. S is mostly used for research and development is statistical methodology where R provides us with an open source implementation of the same.

R gives us a huge range of statistical and graphical tools which can be highly customized. We can realize many machine learning techniques such as classification and clustering of data, linear and polynomial regressions, time-series analysis and tuning complex data models. There are many numerical and statistical analytic software build with are which are currently being used. R is highly scalable and provided easy hookups to big data infrastructures through its packages. Therefore, from simple excel functions to complex predictive modelling, we can do everything with R.

The development community’s strength is reflected by the amount of packages that are available for R. These packages provide specialized techniques, graphical devices, transfer capabilities, dashboard tools, etc. Apart from R, these packages can be written in C++, .NET, Python and java as well. R is available as a “Free Software” under the terms of the Free Software Foundation’s “GNU General Public License”.

**Highlights**

- R can run on any standard operating system
- Very active development and frequent releases
- Provides many packages which can be used as a building blocks for your software
- Provides sophisticated graphical solutions
- Scalable to accommodate big data
- Active community of developers

In conclusion, R is world’s most widely used statistical programming language. Resultantly, it’s the top choice when it comes to data analytics, data mining and statistical programming. Big companies like Facebook, Google, Bank of America, etc. are using R to develop their software’s. Primary users of R are data scientists, software programmers, statisticians and data miners.

These tutorials are written such that even if you have minimal programming knowledge and are using R as a beginner, you can understand all the general basic programming concepts and specific R concepts.

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